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                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
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<div class="textblock">Here is a list of all class members with links to the classes they belong to:</div>

<h3><a id="index_t" name="index_t"></a>- t -</h3><ul>
<li>tag&#160;:&#160;<a class="el" href="structboost_1_1serialization_1_1tracking__level_3_01shark_1_1_typed_flags_3_01_t_01_4_01_4.html#ad363b07d427d2d82c8566877b96c585c">boost::serialization::tracking_level&lt; shark::TypedFlags&lt; T &gt; &gt;</a>, <a class="el" href="structboost_1_1serialization_1_1tracking__level_3_01std_1_1vector_3_01_t_01_4_01_4.html#ad280b44c08dafd0f280ab7b0b87bf6a5">boost::serialization::tracking_level&lt; std::vector&lt; T &gt; &gt;</a></li>
<li>targetSuccessRate()&#160;:&#160;<a class="el" href="classshark_1_1_population_based_step_size_adaptation.html#a427adce1df5a15d76d80b2a19a10fb25">shark::PopulationBasedStepSizeAdaptation</a></li>
<li>targetValue&#160;:&#160;<a class="el" href="structshark_1_1_qp_stopping_condition.html#aef0871941c7b0acd271996801b05b47b">shark::QpStoppingCondition</a></li>
<li>task&#160;:&#160;<a class="el" href="structshark_1_1_multi_task_sample.html#a21d7d05fb180df274599ea6a9cd510a7">shark::MultiTaskSample&lt; InputTypeT &gt;</a></li>
<li>TemperedMarkovChain()&#160;:&#160;<a class="el" href="classshark_1_1_tempered_markov_chain.html#ae2697b357a9b0a540b10fc5437caf910">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>test()&#160;:&#160;<a class="el" href="classshark_1_1_typed_flags.html#a790dadd43f10baf9d14e37badedd4400">shark::TypedFlags&lt; Flag &gt;</a></li>
<li>testShrinkVariable()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#ae85edb4b01745005489b5ced51e4253e">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#abb9d0ed983afddf9bcc3b856c8b04b02">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>threshold()&#160;:&#160;<a class="el" href="classshark_1_1_binary_tree.html#ad7e43f9fa135d67d1817b2a7aa20b434">shark::BinaryTree&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_r_o_c.html#ac88209bb77c813352b590d89a8173b5d">shark::ROC</a></li>
<li>Timer()&#160;:&#160;<a class="el" href="classshark_1_1_timer.html#a58e306564b232e85ad13d49b59ce42c5">shark::Timer</a></li>
<li>toState()&#160;:&#160;<a class="el" href="structshark_1_1_state.html#a9847e65e063245c6b02371c8b84f8da3">shark::State</a></li>
<li>TournamentSelection()&#160;:&#160;<a class="el" href="structshark_1_1_tournament_selection.html#a51ab39ce52c60251c12e676f99556e71">shark::TournamentSelection&lt; Predicate &gt;</a></li>
<li>tournamentSize&#160;:&#160;<a class="el" href="structshark_1_1_e_p_tournament_selection.html#a49f05d90d2ae533ec3f811582cb41cad">shark::EPTournamentSelection&lt; Ordering &gt;</a>, <a class="el" href="structshark_1_1_tournament_selection.html#a0ced5ff10ee3b9a969e6f015181d5f12">shark::TournamentSelection&lt; Predicate &gt;</a></li>
<li>trace()&#160;:&#160;<a class="el" href="classshark_1_1_normalize_kernel_unit_variance.html#a4be3973e544871a8e7bdf1f77d4670fb">shark::NormalizeKernelUnitVariance&lt; InputType &gt;</a></li>
<li>train()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_trainer.html#a71d3fd2567473d746ecb733d7fa28c7e">shark::AbstractTrainer&lt; Model, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_unsupervised_trainer.html#a0d63179d733c998593e3966ffdf17e62">shark::AbstractUnsupervisedTrainer&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_abstract_weighted_trainer.html#ad35ae0b236c45b73f749285a54288e89">shark::AbstractWeightedTrainer&lt; Model, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_weighted_unsupervised_trainer.html#a45bee6b7311cc2f21edf6e63c8a99f05">shark::AbstractWeightedUnsupervisedTrainer&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_c_svm_trainer.html#a9e801518bfba9d02e0749181a5deb0fc">shark::CSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_epsilon_svm_trainer.html#a51d1821c3f6cedeff400e54f6e2b3b5d">shark::EpsilonSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_fisher_l_d_a.html#ad3bc8d880446350e815a79d63ef95053">shark::FisherLDA</a>, <a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#afc6eff8c84cf39de20aaec579f1716b0">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_mean_classifier.html#a81f1f20f6bedb854fab0193d3174dac2">shark::KernelMeanClassifier&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#a31c7513f29d280ad3165d18100962391">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_lasso_regression.html#acf451db20a82eef8547629c28db9db4e">shark::LassoRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_l_d_a.html#a53609e2f3691ec883cdff5332f213f0a">shark::LDA</a>, <a class="el" href="classshark_1_1_linear_c_svm_trainer.html#abf7128243c28edc04a01f157593ece98">shark::LinearCSvmTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_regression.html#a7ca068abe50a7b1eb03305e2cc21c4c5">shark::LinearRegression</a>, <a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#a9e5711480e4f1e214ff3c30a9604d10a">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_logistic_regression.html#ad7301dbc776c3f6027c95817439dbd66">shark::LogisticRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_missing_feature_svm_trainer.html#a7499797486bf5f13ccf1a29572923cc4">shark::MissingFeatureSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_normalize_components_unit_interval.html#aba27460590d2bad0fed075ae88dc916d">shark::NormalizeComponentsUnitInterval&lt; DataType &gt;</a>, <a class="el" href="classshark_1_1_normalize_components_unit_variance.html#a684b111c701789e332577a6739076c3b">shark::NormalizeComponentsUnitVariance&lt; DataType &gt;</a>, <a class="el" href="classshark_1_1_normalize_components_whitening.html#a7d377bcfec684fa66f719189568e7698">shark::NormalizeComponentsWhitening</a>, <a class="el" href="classshark_1_1_normalize_components_z_c_a.html#a1f7d6ef76cce1d8d85474bbd22452fe2">shark::NormalizeComponentsZCA</a>, <a class="el" href="classshark_1_1_normalize_kernel_unit_variance.html#a4bdc12938183edab9acdfd89bde72286">shark::NormalizeKernelUnitVariance&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_one_class_svm_trainer.html#a89a952d06b2f313359fdde6ba59606e6">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_optimization_trainer.html#ab3cfafba31871515074323c20d501573">shark::OptimizationTrainer&lt; Model, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_p_c_a.html#aeae45267c5bc7a3cda484b203a1f15be">shark::PCA</a>, <a class="el" href="classshark_1_1_perceptron.html#af69c978abe25d13d1cb79e866ef05260">shark::Perceptron&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_ranking_svm_trainer.html#a2a7c219733a19872f9f340bc2051335b">shark::RankingSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_regularization_network_trainer.html#a0c203b749f48be1b99e679ea666ff0c0">shark::RegularizationNetworkTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a4975033b328b481f5bbfa2fea88ddcd9">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#a4c1081a998508d12064ec653130f1a8f">shark::RFTrainer&lt; unsigned int &gt;</a>, <a class="el" href="classshark_1_1_squared_hinge_c_svm_trainer.html#a039491eb212c684d4585db0132545a85">shark::SquaredHingeCSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_squared_hinge_linear_c_svm_trainer.html#a9c7df5c98dee200e4214abac74ad3bab">shark::SquaredHingeLinearCSvmTrainer&lt; InputType &gt;</a></li>
<li>trainer()&#160;:&#160;<a class="el" href="classshark_1_1_c_svm_derivative.html#ac11b2f7acd73f07958e8e1d2de9a73a2">shark::CSvmDerivative&lt; InputType, CacheType &gt;</a></li>
<li>TrainerType&#160;:&#160;<a class="el" href="classshark_1_1_cross_validation_error.html#a4a34b5f3470d34c22ebb804a25641712">shark::CrossValidationError&lt; ModelTypeT, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_c_svm_derivative.html#a854324eaf0093bae8996e5aa0edc3449">shark::CSvmDerivative&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_loo_error.html#a5bc94bd972315845cb98d73988f6d908">shark::LooError&lt; ModelTypeT, LabelType &gt;</a></li>
<li>training()&#160;:&#160;<a class="el" href="classshark_1_1_c_v_folds.html#a71a49586552161e0027348fa3a165310">shark::CVFolds&lt; DatasetTypeT &gt;</a></li>
<li>TrainingError()&#160;:&#160;<a class="el" href="classshark_1_1_training_error.html#a4abe5741e99fa123c17d0fdda45f6b89">shark::TrainingError&lt; PointType &gt;</a></li>
<li>trainingFoldIndices()&#160;:&#160;<a class="el" href="classshark_1_1_c_v_folds.html#a04f39c269ed88cf04953269a022f925a">shark::CVFolds&lt; DatasetTypeT &gt;</a></li>
<li>TrainingProgress()&#160;:&#160;<a class="el" href="classshark_1_1_training_progress.html#a519e14c11c239f4aae0a1d0cf82b792f">shark::TrainingProgress&lt; PointType &gt;</a></li>
<li>trainOffset()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_linear_svm_trainer.html#a5d00f5cfe51a496a1511219d12a4c054">shark::AbstractLinearSvmTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_abstract_svm_trainer.html#ae0c02e31cdae3482f37155eb788eb979">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a>, <a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#aed3f039e3cfb8b26115d75838453707b">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#a09fa50917fb4f3deda0e6b0c29977d07">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#a68fcdf51001257ed05a67d42d2671c10">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a></li>
<li>trainSVM()&#160;:&#160;<a class="el" href="classshark_1_1_one_class_svm_trainer.html#afee764d431c31a7cdf28306ab5c197f7">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>transformInternalNode()&#160;:&#160;<a class="el" href="classshark_1_1_c_a_r_tree.html#a3cb77d15a5e99bfb46b1d5a619e5f533">shark::CARTree&lt; LabelType &gt;</a></li>
<li>transformLeafNode()&#160;:&#160;<a class="el" href="classshark_1_1_c_a_r_tree.html#a2e1416b62cbf5b9704fb0d3ff8e3fa4d">shark::CARTree&lt; LabelType &gt;</a></li>
<li>transitionOperator()&#160;:&#160;<a class="el" href="classshark_1_1_energy_storing_tempered_markov_chain.html#a095ed740b5339a40a8dae97f2119b97b">shark::EnergyStoringTemperedMarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_markov_chain.html#ad09fd04ce6823fcb96d671a5d80f4c32">shark::MarkovChain&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_tempered_markov_chain.html#a26911979f0d57257974d9fc19e2ce5fd">shark::TemperedMarkovChain&lt; Operator &gt;</a></li>
<li>trapArea()&#160;:&#160;<a class="el" href="classshark_1_1_negative_a_u_c.html#a336caed340dd3d3c82e7149091ce0977">shark::NegativeAUC&lt; LabelType, OutputType &gt;</a></li>
<li>Tree&#160;:&#160;<a class="el" href="classshark_1_1_tree_nearest_neighbors.html#a963f6592ded4228aa2a34366b4b5bf15">shark::TreeNearestNeighbors&lt; InputType, LabelType &gt;</a></li>
<li>TreeConstruction()&#160;:&#160;<a class="el" href="classshark_1_1_tree_construction.html#a59a1339479147eec5ea8c780a4cf6ddc">shark::TreeConstruction</a></li>
<li>TreeNearestNeighbors()&#160;:&#160;<a class="el" href="classshark_1_1_tree_nearest_neighbors.html#ad3c362695b3ab2d2ac28934e7901a98c">shark::TreeNearestNeighbors&lt; InputType, LabelType &gt;</a></li>
<li>TreeType&#160;:&#160;<a class="el" href="classshark_1_1_c_a_r_tree.html#aab9958485b60a70fd08e501555bf82ce">shark::CARTree&lt; LabelType &gt;</a></li>
<li>TrustRegionNewton()&#160;:&#160;<a class="el" href="classshark_1_1_trust_region_newton.html#ab4bf5d1daf70ee438d8cbdfa258c3029">shark::TrustRegionNewton</a></li>
<li>TwoNormRegularizer()&#160;:&#160;<a class="el" href="classshark_1_1_two_norm_regularizer.html#a87dd7e7fbc9cc385a253cf663c769143">shark::TwoNormRegularizer&lt; SearchPointType &gt;</a></li>
<li>TwoPointStepSizeAdaptation()&#160;:&#160;<a class="el" href="classshark_1_1_two_point_step_size_adaptation.html#afeae0541cca518119296e0d33927aa07">shark::TwoPointStepSizeAdaptation</a></li>
<li>TypedFeatureNotAvailableException()&#160;:&#160;<a class="el" href="classshark_1_1_typed_feature_not_available_exception.html#ae5c53113172930672a43e0c102c4c49b">shark::TypedFeatureNotAvailableException&lt; Feature &gt;</a></li>
<li>TypedFlags()&#160;:&#160;<a class="el" href="classshark_1_1_typed_flags.html#a9f5438ec9df8530b444597059c657b4b">shark::TypedFlags&lt; Flag &gt;</a></li>
</ul>
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